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ISHNE/EHRA Expert Consensus on Remote Monitoring of Cardiovascular Implantable Electronic Devices (CIEDs)

2012· article· en· W1606714112 on OpenAlexaboutno aff
Sérgio Dubner, Angelo Auricchio, Jonathan S. Steinberg, Panos Vardas, Peter H. Stone, Josép Brugada, Ryszard Piotrowicz, David L. Hayes, Paulus Kirchhof, Günter Breithardt, Wojciech Zaręba, Claudio Schuger, Mehmet K. Aktaş, Michał Chudzik, Suneet Mittal, Niraj Varma

Bibliographic record

VenueAnnals of Noninvasive Electrocardiology · 2012
Typearticle
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCardiac resynchronization therapyDefibrillationCanadian Cardiovascular SocietyReimbursementTelemedicineHeart RhythmIntensive care medicineHeart failureImplantable cardioverter-defibrillatorCardiologyMedical emergencyInternal medicineHealth careMyocardial infarctionEjection fraction

Abstract

fetched live from OpenAlex

We are in the midst of a rapidly evolving era of technology-assisted medicine. The field of telemedicine provides the opportunity for highly individualized medical management in a way that has never been possible before. Evolving medical technologies using cardiac implantable devices with capabilities for remote monitoring permit evaluation of multiple parameters of cardiovascular physiology and risk, including cardiac rhythm, device function, blood pressure values, the presence of myocardial ischaemia, and the degree of compensation of congestive heart failure. Cardiac risk, device status, and response to therapies can now be assessed with these electronic systems of detection and reporting. This document reflects the extensive experience from investigators and innovators around the world who are shaping the evolution of this rapidly expanding field, focusing in particular on implantable pacemakers, implantable cardioverter defibrillators, devices for cardiac resynchronization therapy (both with and without defibrillation properties), loop recorders, and hemodynamic monitoring devices. This document covers the basic methodologies, guidelines for their use, experience with existing applications, and the legal and reimbursement aspects associated with their use. To adequately cover this important emerging topic, the International Society for Holter and Noninvasive Electrocardiology and the European Heart Rhythm Association combined their expertise in this field. We hope that the development of this field can contribute to improve care of our cardiovascular patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.539
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.071
GPT teacher head0.348
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations46
Published2012
Admission routes1
Has abstractyes

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